Section 4.1 Euclidean n-Space.

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Presentation transcript:

Section 4.1 Euclidean n-Space

n-SPACE If n is a positive integer, then an ordered n-tuple is a sequence of n real numbers (a1, a2, a3, . . . , an). The set of all ordered n-tuples is called n-space and is denoted by Rn.

EQUALITY, ADDITION, AND SCALAR MULTIPLICATION Two vectors u = (u1, u2, . . . , un) and v = (v1, v2, . . . , vn) in Rn are equal if u1 = v1, u2 = v2, . . . , un = vn. The sum u + v is defined by u + v = (u1 + v1, u2 + v2 , . . . , un + vn) and if k is any scalar, the scalar multiple ku is defined by ku = (ku1, ku2, . . . , kun).

ZERO VECTOR, NEGATIVE VECTORS, AND DIFFERENCE The zero vector in Rn is denoted by 0 and is defined to be 0 =(0, 0, . . . , 0). If u = (u1, u2, . . . , un) , then the negative (or additive inverse) of u is denoted by −u and is defined to be −u = (−u1, −u2, . . . , −un). The difference of vectors in Rn is defined by v − u = v + (−u) or, in terms of components, v − u = (v1 − u1, v2 − u2 , . . . , vn − un).

PROPERTIES OF VECTORS IN Rn Theorem 4.1.1: If u = (u1, u2, . . . , un), v = (v1, v2, . . . , vn) and w = (w1, w2, . . . , wn) are vectors in Rn and k and l are scalars, then: (a) u + v = v + u (b) (u + v) + w = u + (v + w) (c) u + 0 = 0 + u = u (d) u + (−u) = 0; i.e., u − u = 0 (e) k(lu) = (kl)u (f) k(u + v) = ku + kv (g) (k + l)u = ku + lu (h) 1u = u

EUCLIDEAN INNER PRODUCT If u = (u1, u2, . . . , un) and v = (v1, v2, . . . , vn) are any vectors in Rn, then the Euclidean inner product u ∙ v is defined by u ∙ v = u1v1 + u2v2 + . . . + unvn.

EUCLIDEAN n-SPACE Rn with the operations of addition, scalar multiplication, and the Euclidean inner product is referred to as Euclidean n-space.

PROPERTIES OF THE EUCLIDEAN INNER PRODUCT Theorem 4.1.2: If u, v, and w are vectors in Rn and k is any scalar, then: (a) u ∙ v = v ∙ u (b) u ∙ (v + w) = u ∙ v + u ∙ w (c) (ku) ∙ v = k(u ∙ v) (d) v ∙ v ≥ 0. Further, v ∙ v = 0 if and only if v = 0.

LENGTH AND DISTANCE The Euclidean norm (or Euclidean length) of a vector u = (u1, u2, . . . , un) in Rn is defined to be The Euclidean distance between the points u = (u1, u2, . . . , un) and v = (v1, v2, . . . , vn) in Rn is defined by

CAUCHY-SCHWARZ INEQUALITY IN Rn Theorem 4.2.3: If u = (u1, u2, . . . , un) and v = (v1, v2, . . . , vn) are vectors in Rn , then |u ∙ v| ≤ ||u|| ||v||.

PROPERTIES OF LENGTH IN Rn Theorem 4.1.4: If u and v are vectors in Rn and k is any scalar, then: (a) ||u|| ≥ 0 (b) ||u|| = 0 if and only if u = 0 (c) ||ku|| = |k| ||u|| (d) ||u + v|| ≤ ||u|| + ||v|| (Triangle inequality)

PROPERTIES OF DISTANCE Theorem 4.1.5: If u, v, and w are vectors in Rn and k is any scalar, then: (a) d(u, v) ≥ 0 (b) d(u, v) = 0 if and only if u = v (c) d(u, v) = d(v, u) (d) d(u, v) ≤ d(u, w) + d(w, v) (Triangle inequality)

A THEOREM Theorem 4.1.6: If u and v are vectors in Rn with the Euclidean inner product, then

ORTHOGONAL VECTORS Two vectors u and v in Rn are called orthogonal if and only if u ∙ v = 0.

PYTHAGOREAN THEOREM IN Rn Theorem 4.1.7: If u and v are orthogonal vectors in Rn with the Euclidean inner product, then